Residual Parameter Transfer for Deep Domain Adaptation

@article{Rozantsev2018ResidualPT,
  title={Residual Parameter Transfer for Deep Domain Adaptation},
  author={Artem Rozantsev and M. Salzmann and P. Fua},
  journal={2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  year={2018},
  pages={4339-4348}
}
  • Artem Rozantsev, M. Salzmann, P. Fua
  • Published 2018
  • Computer Science
  • 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
  • The goal of Deep Domain Adaptation is to make it possible to use Deep Nets trained in one domain where there is enough annotated training data in another where there is little or none. Most current approaches have focused on learning feature representations that are invariant to the changes that occur when going from one domain to the other, which means using the same network parameters in both domains. While some recent algorithms explicitly model the changes by adapting the network parameters… CONTINUE READING

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